Nvidia · Google · VentureBeat AI
The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs
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Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics.
Key facts
- Technology/Software is the largest industry at 26%, followed by Healthcare/Life Sciences (15%), Financial Services (13%), and Retail/E-commerce (12%)
- Back then, usage of the AI-specialized clouds was equally marginal, CoreWeave at 3%, Lambda at 4%, Crusoe at 2% of enterprises
- Meanwhile the compute already in place runs cold, 83% report GPU utilization of 50% or less, and fewer than half (44%) can rigorously track what their AI compute costs
- Only 12% clear the 50% mark, and a further 8% do not measure utilization at all
Summary
This wave of VentureBeat Pulse Research examines enterprise AI infrastructure and compute: where organizations are in their deployment journey, what they run AI on today, how satisfied they are, what would make them switch, where they plan to evaluate their investments, and, most revealingly, how well they can measure and control the economics of the compute underneath it all. The central finding is a compute gap, the distance between how aggressively enterprises are investing in AI infrastructure and how little of its economics they can see. Enterprises are not settled on their infrastructure vendors, either: A clear majority (64%) plan to switch or add an infrastructure provider within twelve months, and 38% within the next quarter, unusually high churn intent for a category this foundational.